Stochastic approach to system dynamics and its effect on managerial decision making

Rajat Dhawan

The theory of systems thinking has provided tools and techniques for better understanding of complex systems. Most of these are now well established and have been used since the past forty years. One such technique is System Dynamics (SD) which was developed at MIT by J. W. Forrester. Its focus is to study feedback loops in complex systems and the patterns of behaviour generated by them; it aims at improving the mental models of decision makers. Since its creation, the technique has been successfully applied to many types of complex systems, though much focus remains on business and corporate policy.

SD models use deterministic values of variables (non-deterministic have been sparingly used). However, "determinism" is untrue for real business settings. Deterministic variables are unable to capture the true behaviour of a variable as opposed to the ones represented through probability distributions. This results in lack of complete information and is one of the handicaps while making decisions. This research introduces a new method of risk analysis in SD models. The technique performs a probabilistic analysis of key variables in SD modelling and then analyses the change in decision making when characteristics of the probability distribution are altered. In essence it combines probabilistic approach with traditional sensitivity analysis. The information generated by this technique could produce "complete" information thereby improving the mental models of decision makers. The combination of complexity and uncertainty results often in a sub-optimal decision. These researches lead to a concrete argument for testing the effect of the above technique on human decision making through experiments. Hence the focus of the research is twofold - to introduce the notion of a new technique and to discuss the effect of this technique on managerial decision making. It is hoped that this SD-based technique would be instrumental in producing relevant information that would help in improving managers' mental models thereby resulting in better decisions under uncertainty in complex business environments.